The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

Schiff base N,N'-Bis-(4-dimethylamino-benzylidene)-benzene-1,4-diamine has been synthesized from 4-dimethylaminobenzenaldehyde and benzene-1,4-diamine. The structure of Schiff base was obtained by (C.H.N.) microanalysis, Mass, 1HNMR, FT-IR and UV-Vis spectral methods and thermal analysis. Metal mixed ligand complexes of some metal(II) salts with Schiff base ligand and anthranilic acid were prepared in the molar ratio (1:2:2), (Metal):(SBL)2:(Anthra)2, (SBL)= Schiff base ligand, (Anthra) =anthranilic acid and Metal= Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II). The thermal behaviour (TGA) of the complexes was studied. The prepared complexes identified by using mass, thermal analysis, FT.IR and UV-Vis spectrum methods, on otherwise flame

The preparation, spectroscopic characterisation of complexes derived from the mixed ligands with CdII, ZnII and CoII metal ions with Schiff base, Dithiocarbamates (DTCs) and 8-Hydroxyquinoline are reported. The compounds that prepared have been defined via; chloride content, F.T-IR, UV-Vis 1H-NMR spectroscopy and C.H.N.S, as well as conductance and magnetic susceptibility.All data which collected from such methods specified complexes with 6 coordinates in solution and solid states. The biologicalactivity that is related to all the prepared compounds which were screened for their antimicrobial activitiesagainst (G+ and (G-)). The data that collected from biological activity indicate that complexes will have extra activity against such tested

The preparation, spectroscopic characterisation of complexes derived from the mixed ligands with CdII, ZnII and CoII metal ions with Schiff base, Dithiocarbamates (DTCs) and 8-Hydroxyquinoline are reported. The compounds that prepared have been defined via; chloride content, F.T-IR, UV-Vis 1H-NMR spectroscopy and C.H.N.S, as well as conductance and magnetic susceptibility.All data which collected from such methods specified complexes with 6 coordinates in solution and solid states. The biologicalactivity that is related to all the prepared compounds which were screened for their antimicrobial activitiesagainst (G+ and (G- )). The data that collected from biological activity indicate that complexes will have extra activity against such teste

Background: Removal of bacteria from the pulp system by instrumentation of an infected root canal, will be significantly reduced the number of bacteria, but it is well documented that instrumentation alone can-not clean and kill all bacteria found on the root canal walls. Antibacterial irrigants are needed to kill the remaining microorganisms. The aims of this study was to assess antibacterial effect of titanium tetrafluoride (TiF4) solution and brewing green tea against root canal bacteria and to compare with sodium hypochlorite and normal saline through microbiological and molecular studies. Materials and methods: Microbiological study was carried out to determine the concentration of titanium tetrafluoride and brewing green tea at which